Proximate Composition and Nutritional Potential of Saba Senegalensis Fruit from Three Climatic Regions in Burkina Faso
Bibliographic record
Abstract
Non-timber forest products such as lianas provide essential nutrients for human health and should be exploited in Burkina Faso. In order to better valorization, this study aimed to investigate the nutritional potential of Saba senegalensis fruit. The samples of fruit were obtained from three climatic regions then biochemical composition and nutritional content of it pulp were analyzed according to standard methods. The results showed that pulps were acidic with pH varying from 2.85±0.12 to 3.16±0.70 and titratable acidity 4.52±0.20% to 4.89±0.40%. Brix degree, moisture content, and ash were ranged respectively from 20.11±1.50% to 23.50±1.10%, 84.50±3.15% to 86.50±4.25%, 4.44±0.30 g/kg to 5.85±0.40 g/kg. Macronutrients contents were 3.89±0.10 to 3.89±0.10 g/kg, 4.65±0.70 to 7.78±0.50 g/kg, 19.44±1.80 to 23.80±1.40 g/kg, 146.40±11.25 to 155.70±14.50 g/kg respectively for lipids, proteins, total fibers and total carbohydrates. Vitamines rates of pulps were respectively 15.50 ± 1.91 to 17.14 ± 1.90 mg/kg, 0.25 ± 0.05 to 0.55 ± 0.08 mg/kg, and 22.6 ± 2.30 to 27.8 ± 2.90 mg/kg for vitamins B6, A and C. Pulp contain of phytonutrient and anti-nutritional factors were 105.18 ± 10.14 to 132.80 ± 15.00 mg/100g and 19.17 ± 1.16 to 39.60 ± 1.10 mg/100g for total polyphenols and flavonoids and yet ranged 105.25 ±5.15 to 121.80 ±2.20 mg/100g, 78.51 ±0.13 to 80.30 ±1.50 mg/100g, and 20.57 ±3.50 to 26.49 ±1.30 mg/100g respectively for phytates, tannins and oxalates. The mineral composition exhibited higher Mg, Ca, and P content as presented in the results. Principal component analysis (PCA) revealed specific variation on nutritional composition of pulp according to climatic zone. The study demonstrates that S. senegalensis is good nutritional source and could contribute to food security.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".